Abstract
Background: Remote control of cellular behavior without genetic modification of target tissues remains a challenge in synthetic biology. Light-based approaches such as optogenetics suffer from limited tissue penetration, while chemogenetic methods lack spatial resolution and require systemic drug delivery. Radio-frequency (RF) signals offer an alternative due to their deeper tissue penetration, but a framework for translating DNA sequences into RF-controlled chemical outputs has not yet been established. Results: We present a frequency-based biological computer that encodes DNA sequences into RF patterns and converts them into chemical signals for controlling natural cells. A 64-codon frequency table was designed using four RF frequencies (10, 20, 30, and 40 MHz), four pulse counts, and four pulse durations. A bidirectional compiler was developed to encode DNA sequences into RF patterns and decode them back with full accuracy. A biological computer was then simulated, incorporating an RF receiver, a logic circuit (AND, OR, XOR, NAND, NOT), a memory unit, and a chemical signal generator. Tissue-level simulations compared artificial and natural signaling under defined parameters. Under the conditions tested (artificial: C0 = 100 nM, spread = 20 µm; natural: C0 = 10 nM, spread = 50 µm), the artificial system yielded 73.7% cellular response, while the natural system yielded 93.5%. The difference was attributed to the spatial distribution of the signal rather than its absolute concentration. These values are simulation predictions and require experimental validation. Conclusions: This work provides a computational framework for frequency-based biological computing, linking DNA sequences to RF-controlled chemical signaling. The approach may support wireless, remotely controlled protein secretion without modifying target cells. Future work will focus on experimental validation and optimization of signal distribution for improved tissue coverage.